Short answer: ChatGPT-5 is sharper, but it won’t read your mind. Clear prompts win. Vague prompts still fail.
- update in ChatGpt5: big Model Consolidation and a smarter Prompt → Router → Model (Low / Medium / High) pipeline.
- Update 2: Surgical Precision = better at following instructions, not better at understanding vague prompts.
- You’ll get great results by adding tiny “router nudges” (simple phrases that tell the system how to think, what to output, and how strict to be).
Model Consolidation (what changed)
Before ChatGpt5
Plus user have access to:
- GPT-40
- GPT-4.1
- GPT-4.5
- GPT-4.1-mini
- 04-Mini
- 04-mini-high
- o3
After ChatGpt5
After ChatGpt5 user have:
- GPT-5
- GPT-5 Thinking Mini
- GPT-5 Thinking
Why this matters: fewer models to choose from; the system routes your prompt to the right level automatically—if you give it the right hints.
ChatGPT-5 ARchitecture (mental model)
Prompt → Router → Model (Low / Medium / High)
- Prompt: what you type.
- Router: a traffic cop that reads your instructions, evaluates difficulty/precision/format, and selects a capability band:
- Low = fast/simple (summaries, quick replies).
- Medium = balanced (light reasoning, lists, basic code).
- High = deep reasoning or Thinking models (multi-step plans, tricky bugs, proofs).
- Model: the engine that actually answers.
Key lesson: The router loves clarity. If your prompt is fuzzy, it may under-route (pick too “Low”) and you’ll get shallow results.
Update 2 (what actually improved)
Update 2:
- Surgical Precision ✅
- Better at following instructions ✅
- Not better to understand vague prompts ❌
So: be explicit. If you need structured JSON, say so. If you need reasoning, say so. If you need citations, say so.
Why people STILL get prompts wrong (and quick fixes)
- They ask for everything at once.
Fix: one job per prompt: “Summarize the article in 5 bullets for a non-technical audience.” - They forget the audience and format.
Fix: “Audience: beginners. Output: a 6-step checklist.” - They don’t set strict constraints.
Fix: “Max 120 words. No metaphors. Use numbered steps.” - They expect mind-reading.
Fix: add examples: “Example of desired tone: calm, teacherly.” - They don’t nudge the router.
Fix: explicitly hint depth: “Depth: High; require chain-of-thought style reasoning kept internal—return only final steps as bullet points.”
Router Noudge Prhases (tiny phrases that make a big difference)
Copy-paste these lines into your prompts:
- Task Type: “Classify / Summarize / Plan / Debug / Generate code.”
- Audience: “Kids / Non-technical / Exec / Developer.”
- Depth: “Model LOw, medium , hight (prefer Medium unless ambiguity; escalate to High for reasoning).”
- Format: “Output as 5 bullets” or “Return valid JSON only.”
- Limits: “≤120 words” or “No filler.”
- Quality Bar: “Reject if missing data; ask one clarifying question first.”
- Safety: “If uncertain, state assumptions explicitly.”
Tip: If your plan or UI allows manual selection, choose GPT-5 Thinking (or High) for tough reasoning; use GPT-5 (or Medium/Low) for speed.
Prompt recipes (beginner-friendly)
1) Fast summary (Low)
“Task: Summarize. Audience: beginners. Format: 4 bullets, plain language. Limit: ≤80 words. No jargon.”
2) Brainstorm ideas (Medium)
“Task: Brainstorm 10 app ideas. Audience: solo developer. Constraints: <$100/mo tools, buildable in 2 weeks. Format: table: idea | why it’s feasible | first users.”
3) Deep reasoning (High / Thinking)
“Task: Diagnose flaky tests in a Node project. Depth: High. Steps: propose 3 likely causes → show one minimal repro → output a prioritized fix list. Format: numbered list.”
4) Structured output (for automation)
“Task: Extract fields. Format: JSON only with keys: name, date_iso, price_float. **Reject if any field missing.”
5) Write like a teacher
“Task: Explain binary search to kids. Audience: 10-year-olds. Format: 5 short steps + 1 real-life analogy. Limit: ≤120 words.”
6) Coding help with tests
“Task: Write a Python function + 3 pytest tests. Format: single code block. Constraint: O(n) time, O(1) space. **Reject if complexity exceeded.”
7) Interview drill (you vs. coach)
“Role: interviewer. Task: ask 5 DS&A questions, one at a time. Depth: Medium→High if I struggle. Format: after each answer, give a 2-line hint then a 3-line review.”
Mini checklist
- Did I say the Task, Audience, and Format?
- Did I set Depth (Low / Medium / High or GPT-5 vs GPT-5 Thinking)?
- Did I add limits (word count, bullets, JSON)?
- Did I include a small example of the tone/output?
- Did I ask the model to state assumptions or ask 1 question if unclear?
Final takeaway
ChatGPT-5 didn’t make vague prompts magically good. It made clear prompts insanely effective. Tell the router your task, your audience, your format, and your depth—and watch the quality jump.
